Xiaoli Zhao, Ye Fan, Ming Fang

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Xiaoli Zhao, Ye Fan, Ming Fang Impact of Environmental Policies on the Stock Prices of Energy Companies Xiaoli Zhao, Ye Fan, Ming Fang 赵晓丽 范烨 方明 Oct. 23. 2016 Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

2. Description of Environmental Regulation 3. Hypothesis 4. Data 1. Introduction 2. Description of Environmental Regulation 3. Hypothesis 4. Data 5. Methodology 6. Empirical results 7. Conclusions Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

1. Introduction China is facing burdens of environmental pollution and carbon emission Government environmental regulations are counted as an important and effective strategy Environmental regulations alter the corporate’s inner organization and influence outside investors’ perception Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

1. Introduction Environmental regulations are assumed as a burden which effect productivity and competitiveness (Palmer et al., 1995) Break the optimized allocation of resources Nonprofit activities (Gray and Shadbegian, 1995; Haveman and Christiansen, 1981) Environmental fines and lawsuits (Stewart, 1993; Gray and Shadbegian, 1995; Haveman and Christiansen, 1981;Thomas and Zhao, 2009) Crowd out potential investment or innovation (Jaffe and Palmer, 1997; Thomas, 2009) Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

1. Introduction (Motoko and Yang, 2010; Liu et al, 2007) Environmental regulations represent unique opportunities for enterprise competitiveness Popular in green consumers and green markets (Huang and Kung 2010; Jose and Lee 2007) Pollution is wrong placed resources (Porter & van der Linde, 1995) Green mutual funds and green credits (Motoko and Yang, 2010; Liu et al, 2007) Avoid conflicts with local communities, government agencies and public media; (Porter & van der Linde, 1995; Gorski ,1986; Zhang, B. et al.,2011) Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

1. Introduction Market value of listed energy companies Environmental regulations Market value of listed energy companies Affect? Not Affect? Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

2. Description of Environmental Regulation China’s government has gradually established an integrated policy system including Command-and-control regulation (CCR) Legal based policy and administrative based policy Market based regulation (MBR) Environmental information disclosure (EID) Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

2. Description of Environmental Regulation We selected 14 significant environmental policies from 2007 to 2015 in China and 6 important time points MBR: 2 Long-term development plan for renewable energy in Jun. 7. 2007 CCR: Administrative 5 Legislative 11 Publish environmental administrative penalties in Jan.19. 2010. Air pollution Law in Aug. 29. 2015 EID: 3 Main pollutants emission in China, 2011 Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

3. Hypothesis H1: Environmental regulation has a negative impact on energy companies. H2: The negative impact of MBR and EID is less than that of CCR. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

3. Hypothesis H3: Environmental regulation has greater negative impacts electricity and coal companies than oil and gas. H4: Environmental regulations have weaker negative influence on companies of higher EID level. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

3. Hypothesis H5: The higher proportion of state owned, the less negative impacts of environmental regulation are. H6: Environmental regulation has a greater negative impact on energy companies in eastern and middle regions than that in western regions of China. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

3. Hypothesis H7: The negative impact of environmental regulation on the stock price of small-scale and large-scale companies is weaker than that of middle-scale. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

4. Data Electricity companies, coal companies, oil & gas companies 52 companies are selected from the total 93 listed companies The data is collected from China Stock Market Accounting Research (CSMAR) database Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Statistics of listed energy companies 4. Data Statistics of listed energy companies Classification Number The proportion of top 20 percent market capitalization companies The average market capitalization($ hundred million) Listed Energy Companies 52 89.10% 473.5 Industry Electricity 33 38% 82.4 Coal Mining 15 71% 292.5 Oil, gas 4 4378.6 The level of disclosure High 19 90% 114.6 Low 61% 87.2 Area East 30 764.2 Middle 48% 88.7 West 7 33% 52.2 Market capitalization ($ Billion) V<5 22 29.70% 26.4 5≤V<10 11 25.60% 69.6 V≤10 85.20% 1225.1 Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

4. Data The distribution of shareholding proportion of the listed energy companies owned by governments. Figure 1: Distribution of shareholding proportion of governments in listed energy companies Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

5. Methodology Event study is a research methodology designed to measure the impact of an event of interest on stock returns. Dolley (1933), Fama (1969), Mackinlay (1997) explains this method in detail. To date using a market model, several researchers have performed event studies on the day of the announcement pertaining to environmental information — Arora (2001), Gupta and Goldar (2005), and Klassen and McLaughlin (1996). Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

5. Methodology Event study contains six steps. 1. Define event and time window 2. Identify research samples Estimation period Event day Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

5. Methodology 3. Determine share returns model. From the raw daily data, share returns were calculated according to the formula: where is the share return for firm i on day t and is the share price for day t. (1) Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

5. Methodology 4. Estimate the abnormal returns. The expected returns is obtained from the market model and EGARCH model (Nelson,1991). The abnormal returns ARi,t is obtained from the formula 4. (2) (3) (4) Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

5. Methodology   (5) Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

5. Methodology 5. Inspection of significant abnormal returns. To test the null hypothesis that the event does not affect the returns, we use the following J-statistics: (7) Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Table 4: CAAR differences (%) and absolute J-statistics 6. Empirical results Table 4: CAAR differences (%) and absolute J-statistics All the companies Environmental Policies Industry The level of disclosure estimation window event window CAAR/J-ratio Market based regulation Administrative Control Legislative control Information disclosure Electricity, heat production Coal Mining Oil, gas exploration High Low 240 [-2,2] CAAR -0.005*** 0.013* 0.007* -0.013*** -0.011** -0.008** -0.003 -0.002 -0.008*** -0.004 J-ratio (-2.694) (1.777) (1.703) (-4.113) (-2.060) (-2.435) (-1.591) (0.401) (-2.647) (-1.360) [-4,4] -0.010*** 0.006 -0.022*** 0.005 -0.015*** -0.012 (-3.652) (-0.252) (0.692) (-4.885) (0.485) (-3.553) (-1.029) (-0.932) (-3.253) (-2.093) [-6,6] -0.019*** -0.044*** -0.005 -0.034*** 0.053*** -0.029*** -0.006* 0.003 -0.024*** -0.016*** (-5.367) (-3.247) (-1.370) (-6.616) (5.170) (-5.542) (-1.739) (0.160) (-4.187) (-3.552) [-8,8] -0.012*** -0.028* 0.010 -0.028*** 0.042*** -0.010* -0.020*** -0.007 (-2.992) (-1.869) (1.166) (-4.965) (3.687) (-2.642) (-1.939) (0.768) (-3.127) (-1.383) [-10,10] -0.006 -0.042*** 0.018** 0.049*** -0.008 -0.012* (-1.403) (-2.730) (2.130) (-3.267) (3.910) (-1.074) (-0.923) (-0.150) (-1.707) (-0.466) [-20,20] -0.045* 0.016 0.042** 0.033 -0.019** (-0.549) (-1.888) (1.491) (-1.712) (2.387) (-0.543) (-0.894) (1.622) (-2.008) (0.807) 200 -0.005** 0.015** 0.009** -0.012** -0.007** -0.001 (-2.350) (2.015) (2.263) (-4.017) (-2.214) (-2.203) (0.555) (-2.530) (-1.021) 0.008 -0.021*** 0.002 -0.007* (-3.466) (-0.262) (1.126) (-4.776) (0.149) (-3.512) (-0.761) (-0.911) (-3.184) (-1.911) -0.018*** -0.046*** -0.032*** 0.050*** -0.027*** (-5.025) (-3.365) (-0.878) (-6.277) (4.843) (-5.310) (-1.471) (0.195) (-3.926) (-3.323) -0.011*** -0.027* 0.011 0.038*** -0.017*** -0.008* (-2.960) (-1.785) (1.287) (-4.892) (3.333) (-2.770) (-1.703) (0.797) (-3.155) (-1.321) 0.021** 0.043*** (-1.418) (-2.724) (2.469) (-3.313) (3.471) (-1.105) (-0.893) (-0.175) (-1.689) (-0.500) -0.043* 0.014 0.038* -0.018* 0.007 (-0.455) (-1.843) (1.331) (-1.672) (2.816) (-0.280) (-1.234) (1.931) (-1.897) (0.845) Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Table 4 (continue): CAR differences(%) and absolute J-statistics 6. Empirical results Table 4 (continue): CAR differences(%) and absolute J-statistics   State-owned proportion Area Market capitalization (hundred million of RMB ¥) estimation window event window CAAR/J-ratio 10%-30% 30%-50% 50%-70% 70%-90% East Middle West V<5 50≤V<100 V>100 240 [-2,2] CAAR -0.011* -0.007 -0.004 -0.003 -0.007*** -0.000 -0.005 -0.013*** -0.001 J-ratio (-1.812) (-1.631) (-1.491) (-0.260) (-2.621) (-1.171) (-0.254) (-1.450) (-2.598) (-0.870) [-4,4] -0.022** -0.012** -0.008** -0.012*** -0.008* -0.011** -0.020*** (-2.496) (-2.088) (-2.032) (0.090) (-3.262) (-1.699) (-0.731) (-2.465) (-2.695) (-1.290) [-6,6] -0.037*** -0.023*** -0.015*** 0.005 -0.024*** -0.015** -0.002 -0.019*** -0.028*** -0.014** (-3.375) (-3.504) (-3.092) (0.787) (-5.186) (-2.546) (-0.220) (-3.585) (-3.216) (-2.534) [-8,8] -0.025* -0.012 0.014 -0.008 -0.010* -0.023** (-1.929) (-1.640) (-2.447) (1.328) (-3.699) (-1.362) (1.444) (-1.846) (-2.175) (-1.273) [-10,10] -0.017 0.008 0.022** (-0.460) (-1.091) (0.627) (-2.489) (-0.486) (2.018) (-0.851) (-1.048) (-0.586) [-20,20] -0.015 0.003 0.023* -0.010 -0.009 (-0.784) (-0.267) (-0.427) (0.929) (-1.467) (-0.200) (1.843) (0.379) (-0.711) (-0.788) 200 -0.006 -0.006** (-1.651) (-1.548) (-1.186) (-0.107) (-2.329) (-0.942) (-0.248) (-1.337) (-2.310) (-0.645) -0.007* -0.010** -0.019** (-2.461) (-2.207) (-1.703) (0.069) (-3.072) (-1.542) (-0.848) (-2.340) (-2.568) (-1.218) -0.035*** -0.022*** -0.014*** 0.004 -0.018*** -0.026*** (-3.153) (-3.407) (-2.888) (0.748) (-4.716) (-2.542) (-0.258) (-3.358) (-2.982) (-2.399) -0.024* -0.012* 0.012 -0.009* -0.021** (-1.896) (-2.426) (1.411) (-3.612) (-1.298) (1.264) (-1.748) (-2.056) (-1.427) -0.016 0.006 0.021* -0.011 (-1.214) (-0.598) (-0.975) (0.593) (-0.500) (1.917) (-0.941) (-0.950) (-0.590) 0.015 0.024* (-0.513) (0.025) (-0.726) (1.043) (-1.488) (0.048) (1.767) (0.353) (-0.245) (-0.981) Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

6. Empirical results H1 is supported. Figure 2 Impact of total environmental policies on the stock price of listed energy companies Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

6. Empirical results H2 is rejected Figure 3: Impact of different environmental policies on the stock price of listed energy companies Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

6. Empirical results H3 is supported. Figure 4: Impact of environmental regulation on the stock price of different kinds of energy companies Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

6. Empirical results H4 is rejected. Figure 5: Impact of environmental regulation on the stock price of energy companies with different EID Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

6. Empirical results H5 is supported. Figure 6: Impact of environmental regulation on the stock price of energy companies with different state share Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

6. Empirical results H6 is supported. Figure 7: Impact of environmental regulation on the stock price of energy companies in different regions Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

6. Empirical results H7 is supported. Figure 8: Impact of environmental regulation on the stock price of energy companies with different scales Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

6. Empirical results Robustness Checks of Abnormal Daily Volume Event window AADV Market Based Regulation Administrative Regulation Legislative Regulation Information Disclosure All policies Panel A: Average abnormal daily volume (AADV) [-2,2] 0.678*** -0.033 0.404*** -0.291*** 0.253*** (7.202) (-1.035) (9.426) (-8.602) (8.930) [-4,4] 0.810*** -0.100*** 0.390*** -0.343*** 0.236*** (10.507) (-5.520) (12.508) (-12.809) (11.072) [-6,6] 0.866*** -0.121*** 0.374*** -0.334*** 0.229*** (11.722) (-8.149) (14.296) (-14.918) (12.345) [-8,8] 0.936*** -0.136*** 0.402*** -0.356*** 0.245*** (13.156) (-10.487) (17.304) (-18.560) (14.770) Panel B: Average daily volume shifts(ADVS) 0.963 0.126*** 0.064*** 0.071** 0.170** (1.118) (6.790) (5.376) (2.156) (2.280) 0.626 0.054*** 0.093*** 0.079*** 0.135*** (1.392) (4.131) (8.359) (3.224) (3.355) 0.409 0.063*** 0.095*** 0.092*** 0.118*** (1.312) (5.701) (8.176) (4.795) (4.253) 0.351 0.086*** 0.123*** 0.068*** 0.131*** (1.489) (8.443) (7.585) (4.359) (5.841) Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

7. Conclusions Environmental regulation has a negative impact on energy companies. The negative effect of MBR and EID is not less than that of CCR. Environmental regulation has greater negative effects on electricity and coal than oil and gas. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

7. Conclusions Environmental regulations don’t have weaker negative influence on the companies that have higher EID levels. The higher proportion of state owned, the less negative effects of environmental regulation. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

7. Conclusions Environmental regulation has a greater negative effect on the companies in eastern and middle regions than that in western regions in China. The negative impact of environmental regulations on the stock price of small-scale and large-scale companies is weaker than that of middle-scale. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Ye Fan 范烨 E-mail: Fanyecup@foxmail.com Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing